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【ECCV2016】Detecting Text in Natural Image with Connectionist Text Proposal Network
時間 2021-01-16
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關鍵點 文本檢測和一般目標檢測的不同——文本是一個sequence(字符、字符的一部分、多字符組成的一個sequence),同一文本線上不同字符可以互相利用上下文,可以用sequence的方法。比如RNN來表示。作者認爲,預測文本的豎直位置(文本bounding box的上下邊界)比水平位置(文本bounding box的左右邊界)更容易。 Top-down(先檢測文本區域,再找出文本線)的文本檢
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相關文章
1.
【Paper Reading】【CTPN: Detecting Text in Natural Image with Connectionist Text Proposal Network】
2.
CTPN(Detecting Text in Natural Image with Connectionist Text Proposal Network)算法詳解
3.
[論文閱讀] CTPN---Detecting Text in Natural Image with Connectionist Text Proposal Network
4.
Detecting Text in Natural Image with Connectionist Text Proposal Network論文筆記
5.
翻譯CTPN:Detecting Text in Natural Image with Connectionist Text Proposal Network
6.
論文閱讀學習 - CTPN-Detecting Text in Natural Image with Connectionist Text Proposal Network
7.
Connectionist Text Proposal Network
8.
明亮如星研旅(1)——Detecting Text in Natural Scenes with Stroke Width Transform
9.
論文閱讀CENet-Detecting Text in the Wild with Deep character Embedding Network
10.
CVPR2017《Detecting Oriented Text in Natural Images by Linking Segments》閱讀筆記
>>更多相關文章<<